Fuzzy self-tuning PID control of the operation temperatures in a two-staged membrane separation process

A two-staged membrane separation process for hydrogen recovery from refinery gases is introduced. The principle of the gas membrane separation process and the influence of the operation temperatures are analyzed. As the conventional PID controller is difficult to make the operation temperatures steady, a fuzzy self-tuning PID control algorithm is proposed. The application shows that the algorithm is effective, the operation temperatures of both stages can be controlled steadily, and the operation flexibility and adaptability of the hydrogen recovery unit are enhanced with safety. This study lays a foundation to optimize the control of the membrane separation process and thus ensure the membrane performance.

A Design of a PID Self-Tuning Controller Using LabVIEW

In this paper a trial has been made to design a simple self-tuning LabVIEW-based PID controller. The controller uses an open-loop relay test, calculates the tuned parameters in an open loop mode of operation before it updates controller parameters and runs the process as a closed-loop system. The controller reacts on a persistent offset error value as a result of load disturbance or a set point change. Practical results show that such a controller may be recommended to control a variety of industrial processes. A GUI was developed to facilitate control-mode selection, the setting of controller parameters, and the display of control system variables. GUI makes it possible to put the controller in manual or self-tuning mode.

Neural Model-Based Self-Tuning PID Strategy Applied to PEMFC

This paper illustrates the benefits of a self-tuning PID strategy applied to a proton exchange membrane fuel cell system. Controller parameters are updated on-line, at each sampling time, based on an instantaneous linearization of an artificial neural network model of the process and a General Minimum Variance control law. The self-tuning PID scheme allows managing nonlinear behaviors of the system while avoiding heavy computations. The applicability, efficiency and robustness of the proposed control strategy are experimentally confirmed using varying control scenarios. In this aim, the original built-in controller is overridden and the self-tuning PID controller is implemented externally and executed on-line. Experimental results show good performance in setpoint tracking accuracy and robustness against plant/model mismatch. The proposed strategy appears to be a promising alternative to heavy computation nonlinear control strategies and not optimal linear control strategies.

Development of an Enhanced Self-Tuning RBF-PID Controller for Achieving Higher Energy-Efficient Process Control

Proportional, integral and derivative (PID) control strategy has been widely applied in heating systems in decades. To improve the accuracy and the robustness of PID control, self-tuning radial-basis-function neural network PID (RBF-PID) is developed and used. Even though being popular, during the control process both of PID and RBF-PID control strategy are inadequate in achieving simultaneous high energy-efficiency and good control accuracy. To address this problem, in this paper we develop and report an enhanced self-tuning radial-basis-function neural network PID (e-RBF-PID) controller. To identify the superiority of e-RBF-PID, following works are conducted and reported in this paper. Firstly, four controllers, i.e., on-off, PID, RBF-PID and e-RBF-PID are designed. Secondly, in order to test the performance of the e-RBF-PID controller, an experimental water heating system is constructed for being controlled. Finally, the energy consumption for the four controllers under the three control scenarios is investigated through experiments. The experimental results indicate that in the three scenarios, the developed e-RBF-PID controller outperforms on-off controller as having higher accuracy. Compared to the PID controller, the e-RBF-PID controller has higher speed in control, and the experimental results show that settling time savings is between 12.6% - 49.0%. Most importantly, less control energy consumption is obtained if using the e-RBF-PID controller. It is found that up to 28.5% energy consumption can be saved. Therefore, it is concluded that the proposed e-RBF-PID is capable of enhancing energy efficiency during control process.

基于模糊PID汽车变速箱自动控制方法

为改善汽车变速箱的目标速度跟踪水平,提升汽车的动力性,基于模糊PID汽车变速箱自动控制方法,确定汽车行驶的目标车速,计算目标车速与实际车速之间的偏差,以及速度偏差的变化率,将上述结果作为PID控制器的输入,利用参数整定后的PID控制器,确定汽车变速箱的控制变量,控制汽车传动机构输出理想车速。实验结果表明,汽车以阶跃信号、斜坡信号和正弦信号状态行驶时,该方法均可以精准跟踪汽车变速箱的速比,控制效果与动态跟踪性能优异,为保持汽车的最佳动力性能提供了良好的控制策略。

A novel PID controller tuning method based on optimization technique

An approach for parameter estimation of proportional-integral-derivative(PID) control system using a new nonlinear programming(NLP) algorithm was proposed.SQP/IIPM algorithm is a sequential quadratic programming(SQP) based algorithm that derives its search directions by solving quadratic programming(QP) subproblems via an infeasible interior point method(IIPM) and evaluates step length adaptively via a simple line search and/or a quadratic search algorithm depending on the termination of the IIPM solver.The task of tuning PI/PID parameters for the first-and second-order systems was modeled as constrained NLP problem. SQP/IIPM algorithm was applied to determining the optimum parameters for the PI/PID control systems.To assess the performance of the proposed method,a Matlab simulation of PID controller tuning was conducted to compare the proposed SQP/IIPM algorithm with the gain and phase margin(GPM) method and Ziegler-Nichols(ZN) method.The results reveal that,for both step and impulse response tests,the PI/PID controller using SQP/IIPM optimization algorithm consistently reduce rise time,settling-time and remarkably lower overshoot compared to GPM and ZN methods,and the proposed method improves the robustness and effectiveness of numerical optimization of PID control systems.

Design and Implementation of Digital Fractional Order PID Controller Using Optimal Pole-Zero Approximation Method for Magnetic Levitation System

The aim of this paper is to employ fractional order proportional integral derivative(FO-PID)controller and integer order PID controller to control the position of the levitated object in a magnetic levitation system(MLS),which is inherently nonlinear and unstable system.The proposal is to deploy discrete optimal pole-zero approximation method for realization of digital fractional order controller.An approach of phase shaping by slope cancellation of asymptotic phase plots for zeros and poles within given bandwidth is explored.The controller parameters are tuned using dynamic particle swarm optimization(d PSO)technique.Effectiveness of the proposed control scheme is verified by simulation and experimental results.The performance of realized digital FO-PID controller has been compared with that of the integer order PID controllers.It is observed that effort required in fractional order control is smaller as compared with its integer counterpart for obtaining the same system performance.

PID Parameters for Tuning and Optimization of a Turbine EngineBased on the Simplex Search Method

A PID parameters tuning and optimization method for a turbine engine based on the simplex search method was proposed. Taking time delay of combustion and actuator into account, a simulation model of a PID control system for a turbine engine was developed. A performance index based on the integral of absolute error （IAE） was given as an objective function of optimization. In order to avoid the sensitivity that resulted from the initial values of the simplex search method, the traditional Ziegler-Nichols method was used to tune PID parameters to obtain the initial values at first, then the simplex search method was applied to optimize PID parameters for the turbine engine. Simulation results indicate that the simplex search method is a reasonable and effective method for PID controller parameters tuning and optimization.

SELF-TUNING MEASUREMENT FUSION KALMAN FILTER WITH CORRELATED MEASUREMENT NOISES

For the multisensor system with correlated measurement noises and unknown noise statistics, based on the solution of the matrix equations for correlation function, the on-line estimators of the noise variances and cross-covariances is obtained. Further, a self-tuning weighted measurement fusion Kalman filter is presented, based on the Riccati equation. By the Dynamic Error System Analysis (DESA) method, it rigorously proved that the presented self-tuning weighted measurement fusion Kalman filter converges to the optimal weighted measurement fusion steady-state Kalman filter in a realization or with probability one, so that it has asymptotic global optimality. A simulation example for a target tracking system with 3-sensor shows that the presented self-tuning measurement fusion Kalman fuser converges to the optimal steady-state measurement fusion Kalman fuser.

Adaptive Quasi-PID Control Method for Switching Power Amplifiers

Quasi-PID control method that is able to effectively inhibit the inherent tracking error of PI control method is proposed on the basis of a rounded theoretical analysis of a model of switching power amplifiers (SPAs). To avoid the harmful impacts of the circuit parameter variations and the random disturbances on quasi-PID control method, a single neuron is introduced to endow it with self-adaptability. Quasi-PID control method and the single neuron combine with each other perfectly, and their formation is named as single-neuron adaptive quasi-PID control method. Simulation and experimental results show that single-neuron adaptive quasi-PID control method can accurately track both the predictable and the unpredictable waveforms. Quantitative analysis demonstrates that the accuracy of single-neuron adaptive quasi-PID control method is comparable to that of linear power amplifiers (LPAs) and so can fulfill the requirements of some high-accuracy applications, such as protective relay test. Such accuracy is very difficult to be achieved by many modern control methods for converter controls. Compared with other modern control methods, the programming realization of single-neuron adaptive quasi-PID control method is more suitable for real-time applications and realization on low-end microprocessors for its simple structure and lower computational complexity.

基于模糊控制的闪蒸罐PID控制器设计与仿真

PID控制器依照经验进行整定的方式需要花费大量时间和精力,而工业被控对象大都存在随时间变化、非线性等特性,PID控制的效果并不理想。以闪蒸罐压力控制为研究对象设计FUZZY-PID控制器。仿真结果表明:在PID调节后有超调情况下,FUZZY-PID控制器调节时间缩短约341.80 s,超调量减小约4.62%;在PID调节后无超调情况下,FUZZY-PID控制器调节时间缩短约395.60 s。抗干扰实验结果表明:在加入白噪声后,FUZZY-PID控制器与PID控制器控制效果差距不甚明显,都比较稳定,在同一时刻加入脉冲扰动后,FUZZY-PID控制器所需调节时间较PID控制器缩短约70.70 s,调节时间更短,更加稳定。说明相较于传统PID控制器,FUZZY-PID控制器调节时间更短、超调量更小、更加稳定。

基于模糊PID算法的阀门电动执行器控制方法

由于阀门电动执行器具有非线性、时变性等特点,导致传统控制方法很难达到理想的控制效果,提出基于模糊PID算法的阀门电动执行器控制方法。根据阀门电动执行器的结构特点,建立驱动电机环节的数学模型作为被控对象,在传统PID控制器中加入模糊理论形成模糊PID控制结构,输入相应参数得到控制信号,并将其输出到被控对象中,实现对阀门电动执行器的控制。实验结果表明,在设计方法控制阀门电动执行器的过程中施加突变信号扰动后,仅需0.58 s恢复稳态,证实了该方法抗干扰能力强、控制效果优。

典型二阶系统的单纯形法PID参数优化设计

针对典型二阶系统,提出了一种基于单纯形法的PID参数优化设计方法。通过对目标函数进行建立和分析,将PID控制器引入系统中,再通过使用单纯形法对PID参数进行优化,得到最优的参数组合,以实现对系统的稳定性和性能的优化。实验结果表明,提出的单纯形法得到的最优参数能有效改善二阶系统的控制性能,并具有一定的实用价值。

基于GSA的水轮机调速器PID控制参数优化方法

针对现有水轮机调速器控制参数优化研究依赖系统特征参数值、忽视发电机模型的不确定性以及控制策略较落后等问题,以引力搜索算法(GSA)为基础,对水轮机调速器PID控制参数优化模型和优化方法等进行分析,仿真模拟优化中国某水电机组,比较不同状态下水轮机调速器的组合控制效果。结果表明,在孤网运行条件下,基于GSA的水轮机调速器PID控制参数优化方法对水轮机组动态运行品质的提升效果最佳。

智能PID整定在火电厂热工控制系统中的运用

文章提出基于PM法的PID参数整定法及基于模式识别的专家自整定方法,对PM法整定公式展开改进分析,阐述专家自整定控制器的结构,明确专家系统性能判别方法及各参数的整定规则,再利用热工综合优化平台中的330MW机组仿真平台对两种整定方法的应用展开仿真,总结出智能PID整定技术值得在火电厂热工控制系统中应用推广的结论。

基于模糊PID的室内喷涂机器人末端位姿控制方法

为提高室内喷涂机器人末端位姿控制精度,利用模糊比例-积分-微分(Proportion Integration Differentiation,PID),对室内喷涂机器人末端位姿控制展开研究。建立室内喷涂机器人运动学模型,采集机器人运行过程中的状态变化和外部环境信息,设计模糊PID控制器结构,计算喷涂机器人末端位姿控制输出,驱动机器人末端达到设定位姿。实验结果表明,相比传统控制方法,所提的基于模糊PID的室内喷涂机器人末端位姿控制方法在末端位置坐标的控制上表现出更高的精度和稳定性,末端位置坐标误差最高不超过0.03,能够在不同工况下保持稳定的控制性能。

ADRC FRACTIONAL ORDER PID CONTROLLER DESIGN OF HYPERSONIC FLIGHT VEHICLE

Active disturbance rejection controller（ADRC）uses tracking-differentiator（TD）to solve the contradiction between the overshoot and the rapid nature.Fractional order proportion integral derivative（PID）controller improves the control quality and expands the stable region of the system parameters.ADRC fractional order（ADRFO）PID controller is designed by combining ADRC with the fractional order PID and applied to reentry attitude control of hypersonic vehicle.Simulation results show that ADRFO PID controller has better control effect and greater stable region for the strong nonlinear model of hypersonic flight vehicle under the influence of external disturbance,and has stronger robustness against the perturbation in system parameters.

PID调节器自整定的PM法及其公式推导

本文提出了一种只基于给定相位裕度的自整定方法(简称PM法),并推导出一套相应的自整定公式。对PM法、临界比例度法(简称Z-N法)、理想继电特性法(简称(?)str(¨|o)m法)作了比较性研究,研究结果说明,PM法优于Z-N法和(?)str(¨|o)m法,该法现已用于“玻纤拉丝漏板的智能温度控制仪”的科研项目中,并取得了满意的控制效果。

基于工程整定法的模糊PID

在ＰＩＤ工程整定法的基础上，提出一种基于模糊规则的模糊ＰＩＤ复合控制算法．算法首先根据扩充临界比例法等工程ＰＩＤ整定方法将ＰＩＤ公式简化，然后通过模糊控制规则和模糊推理确定一张模糊控制表，在时实控制中通过对模糊控制表的查询，在线调节ＰＩＤ控制参数．液压电梯的实验和仿真结果表明，本文提出的控制控制算法具有算法简单、控制品质优良等特点．

智能PID方法在高精度控温中的应用研究

论述了智能PID方法的基本原理。该方法将PID控制相结合，可在控制过程中实时修改控制规律和参数。将该方法用于计量行业的高精度温度控制后，取得了良好的控制效果。